gam.parser               package:mgcv               R Documentation

_G_e_n_e_r_a_l_i_z_e_d _A_d_d_i_t_i_v_e _M_o_d_e_l _f_i_t_t_i_n_g _u_s_i_n_g _p_e_n_a_l_i_z_e_d _r_e_g_r_e_s_s_i_o_n _s_p_l_i_n_e_s _a_n_d 
_G_C_V

_D_e_s_c_r_i_p_t_i_o_n:

     This is an internal function of package 'mgcv'. It is a service
     routine for 'gam' which splits of the strictly parametric part of
     the model formula and returns it as a formula and interprets the
     smooth parts  of the model formula.   The processing of  the
     smooth terms results in the return of the basis dimension for each
     smooth term, whether  or not the smooth term is to be treated as a
     pure regression spline (i.e. one without a penalty) and the type
     of basis used to represent the spline. It also returns an array of
     covariate names which are arguments of smooths, and the name of
     the response variable.   For further information on usuage see
     code for 'gam'.

_A_u_t_h_o_r(_s):

     Simon N. Wood simon@stats.gla.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     Gu and Wahba (1991) Minimizing GCV/GML scores with multiple
     smoothing parameters via the Newton method. SIAM J. Sci. Statist.
     Comput. 12:383-398

     Wood, S.N. (2000)  Modelling and Smoothing Parameter Estimation
     with Multiple  Quadratic Penalties. J.R.Statist.Soc.B
     62(2):413-428

     Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B
     65(1):95-114

     <URL: http://www.stats.gla.ac.uk/~simon/>

_S_e_e _A_l_s_o:

     'gam' 'mgcv'

